Artificial Reality Application Lifecycle

ABSTRACT

Aspects of the present disclosure are directed to an artificial reality (XR) application system controlling applications in an artificial reality environment. In various cases, these controls include automatically suggesting XR applications by determining an XR context and identifying applications that match the XR context. These applications can be suggested to a user, who can authorize their execution, setting permissions for the application. In some cases, applications can be divided into components which can be progressively downloaded. By providing application suggestions relevant to the current context and progressively downloading application components, applications can appear ambient, rather than relying on users to constantly download, install, or activate applications. Permissions for applications may be revoked permanently or for certain situations—either through user permissions selections or automatically in response to determined user intents. When multiple applications are simultaneously authorized to execute, the XR application system can employ a ranking system to prevent overcrowding.

TECHNICAL FIELD

The present disclosure is directed to controlling how artificial realityapplications launch, what permissions to give the artificial realityapplications, and establishing priority among the artificial realityapplications.

BACKGROUND

Interaction with computing systems are often founded on a set of coreconcepts that define how users can interact with that computing system.For example, early operating systems provided textual interfaces tointeract with a file directory. This was later built upon with theaddition of “windowing” systems, whereby levels in the file directoryand executing applications were displayed in multiple windows, eachallocated a portion of a 2D display that was populated with contentselected for that window. As computing form factors decreased in sizeand added integrated hardware capabilities (e.g., cameras, GPS, wirelessantennas, etc.) the core concepts again evolved, moving to an “app”focus, where each app encapsulated a capability of the computing system.

Existing artificial reality systems provide models, such as 3D virtualobjects and 2D panels, with which a user can interact in 3D space.Existing artificial reality systems have generally backed these modelsby extending the app core computing concept. For example, a user caninstantiate these models by finding an app in an app store, activatingthe app and telling the app to create the model, and using the model asan interface back to the app. This approach generally requires users tomanually discover apps relevant to their needs and requires continuedexecution of the app for the models to persist in the artificial realityenvironment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an overview of devices on whichsome implementations of the present technology can operate.

FIG. 2A is a wire diagram illustrating a virtual reality headset whichcan be used in some implementations of the present technology.

FIG. 2B is a wire diagram illustrating a mixed reality headset which canbe used in some implementations of the present technology.

FIG. 2C is a wire diagram illustrating controllers which, in someimplementations, a user can hold in one or both hands to interact withan artificial reality environment.

FIG. 3 is a block diagram illustrating an overview of an environment inwhich some implementations of the present technology can operate.

FIG. 4 is a block diagram illustrating components which, in someimplementations, can be used in a system employing the disclosedtechnology.

FIG. 5 is a flow diagram illustrating a process used in someimplementations of the present technology for providing context-basedapplication suggestions and recognizing a user action as anauthorization for a suggested application.

FIG. 6 is a flow diagram illustrating a process used in someimplementations of the present technology for progressive download ofapplication components.

FIG. 7 is a flow diagram illustrating a process used in someimplementations of the present technology for controlling applicationpermissions via an application manager.

FIG. 8 is a flow diagram illustrating a process used in someimplementations of the present technology for controlling applicationpermissions in response to a context.

FIG. 9 is a flow diagram illustrating a process used in someimplementations of the present technology for prioritizing applicationoutput through a context-specific ranking.

FIG. 10 is a conceptual diagram illustrating an example of a userreceiving application suggestions, peeling a suggestion to enable theapplication, and viewing augments from the enabled application.

FIG. 11A is a conceptual diagram illustrating an example of receivingapplication suggestions for a context.

FIG. 11B is a conceptual diagram illustrating an example of receivingauthorization for a selection of a suggested through a drag gesture.

FIG. 11C is a conceptual diagram illustrating an example of anauthorized application generating an augment in relation to a context.

FIG. 12 is a conceptual diagram illustrating an example of anapplication manager.

The techniques introduced here may be better understood by referring tothe following Detailed Description in conjunction with the accompanyingdrawings, in which like reference numerals indicate identical orfunctionally similar elements.

DETAILED DESCRIPTION

Aspects of the present disclosure are directed to an artificial reality(XR) application system controlling applications in an artificialreality environment. In various cases, these controls includeautomatically suggesting XR applications. Such suggestions can beperformed by identifying anchor points in an artificial realityenvironment, determining a current XR context, and identifyingapplications that match the identified anchor points and/or XR context.These applications can be suggested to a user, who can perform variousactions to authorize their execution, setting permissions for theselected application to take actions such as writing content into theartificial reality environment, providing notifications, exchanging datawith other applications, etc. In some implementations, applications canwrite content into the artificial reality environment through“augments.” An “augment” is a 2D or 3D volume, in an artificial realityenvironment, that can include presentation data, context, and logic.Augments and their orchestration are discussed in greater detail U.S.patent application Ser. No. 17/008,478, titled “Artificial RealityAugments and Surfaces,” (filed Aug. 31, 2020) and U.S. patentapplication Ser. No. 17/131,563, titled “Augment Orchestration in anArtificial Reality Environment,” (filed Dec. 22, 2020), each of which isincorporated herein by reference.

In some cases, applications can be divided into components. Thecomponents of applications authorized for execution can be progressivelydownloaded. This allows the application to begin taking actions beforeall of its components are resident on the XR device. For example, whenan application has been authorized and is triggered to create aparticular type of augment, the components for creating and controllingthat augment can be prioritized in the download of its components. Thisallows applications to load upon use, without having to wait forextensive download times.

By providing application suggestions relevant to the current artificialreality environment and context and progressively downloadingapplication components, applications can appear as “ambient,” i.e., withnearly instant access and working as always-on, rather than relying onusers to constantly download, install, or activate applications for usewithin the artificial reality environment. Instead, the artificialreality application system analyzes the environment for various objects,contexts, etc.; downloads and installs applications that the user mayfind useful; and suggests the applications to the user. For example,when a user enters a particular grocery store, the system can check tosee if that store has an application and suggest that application to theuser. The user can then peel that application into her environment foractivation, at which point the application is able to provide directionsto items in the store, nutritional information and recipes for items theuser views, and notices of specials and coupons.

Once an application has been authorized for execution, thatauthorization may be revoked permanently or for certain situations. Theartificial reality application system can provide multiple ways forusers to control which applications can access or manipulate theenvironment. In some cases, a user can access an “application manager”UI with options to find and customize applications enabled on theartificial reality application system. Through the application manager,a user can, for example, search for applications, disable/enableapplications, set timers or events that trigger an application to beenabled/disabled, register/de-register objects and contexts theapplication can control or be made aware of, etc. In someimplementations, the artificial reality application system canautomatically mute or disable an application based on a context such asa threshold number of augments from an application being closed. Forexample, the system can mute messaging applications while the user is ina conversation or disable applications that produce augments the userregularly closes or ignores.

When multiple applications are simultaneously authorized to execute inan artificial reality environment, and in some cases on the same anchorpoints, the artificial reality environment can become cluttered anddifficult to interact with. The artificial reality application systemcan employ a ranking system to limit the amount of augments that can beanchored to a particular surface, object, within a physical space,and/or within an area in the user's field of view. The artificialreality application system can define rankings among the applicationsthat can write to a given anchor or area, where the rankings can accountfor a current context. The context can account for features such as auser context (e.g., user activity/posture, location, social graphconnections to nearby users, calendar events for the user, known userroutines, whether the user in a conversation, where user has beenlooking, user set preferences, etc.) and an artificial realityenvironment context (e.g., surfaces and objects in the artificialreality environment, current time, scene tags such as noisy, crowded,etc.) With the application rankings, and in some cases additional rulesfor allowing application output, the artificial reality applicationsystem can select threshold amounts of output from highest rankingapplications for anchors and spaces.

As an example, multiple applications may be registered to provideinformation about food items (e.g., a recipe application, a dietapplication, and a food product comparison application), however, theartificial reality application system may only allow a single augment tobe attached to any given real-world object. In this example, when a useris looking at two similar food items in a grocery store, the artificialreality application system generates a ranking based on a context of theuser's location (grocery store), user preferences, and other augmentsalready displayed in the artificial reality environment to determinethat the food product comparison application is most likely to be usefulto the user at the moment (i.e., is highest ranked) and is thus allowedto attach an augment to the recognized food item. Later, when the useris looking in her refrigerator at home, the recipe application isdetermined to have a higher ranking for that context and is allowed toplace an augment on a recognized food item.

Embodiments of the disclosed technology may include or be implemented inconjunction with an artificial reality system. Artificial reality orextra reality (XR) is a form of reality that has been adjusted in somemanner before presentation to a user, which may include, e.g., virtualreality (VR), augmented reality (AR), mixed reality (MR), hybridreality, or some combination and/or derivatives thereof. Artificialreality content may include completely generated content or generatedcontent combined with captured content (e.g., real-world photographs).The artificial reality content may include video, audio, hapticfeedback, or some combination thereof, any of which may be presented ina single channel or in multiple channels (such as stereo video thatproduces a three-dimensional effect to the viewer). Additionally, insome embodiments, artificial reality may be associated withapplications, products, accessories, services, or some combinationthereof, that are, e.g., used to create content in an artificial realityand/or used in (e.g., perform activities in) an artificial reality. Theartificial reality system that provides the artificial reality contentmay be implemented on various platforms, including a head-mounteddisplay (HMD) connected to a host computer system, a standalone HMD, amobile device or computing system, a “cave” environment or otherprojection system, or any other hardware platform capable of providingartificial reality content to one or more viewers.

“Virtual reality” or “VR,” as used herein, refers to an immersiveexperience where a user's visual input is controlled by a computingsystem. “Augmented reality” or “AR” refers to systems where a user viewsimages of the real world after they have passed through a computingsystem. For example, a tablet with a camera on the back can captureimages of the real world and then display the images on the screen onthe opposite side of the tablet from the camera. The tablet can processand adjust or “augment” the images as they pass through the system, suchas by adding virtual objects. “Mixed reality” or “MR” refers to systemswhere light entering a user's eye is partially generated by a computingsystem and partially composes light reflected off objects in the realworld. For example, a MR headset could be shaped as a pair of glasseswith a pass-through display, which allows light from the real world topass through a waveguide that simultaneously emits light from aprojector in the MR headset, allowing the MR headset to present virtualobjects intermixed with the real objects the user can see. “Artificialreality,” “extra reality,” or “XR,” as used herein, refers to any of VR,AR, MR, or any combination or hybrid thereof.

Multiple existing computing systems allow users to extend theirfunctionality by installing additional applications. However, theseexisting system generally require a user to manually select, download,and execute applications. This is a time consuming process, it's aprocess that can be impossible for some users to navigate, and it can beextremely difficult to locate an application that is useful and relevantto a current context. Often by the time a user performs these actions,the context for which the application was desired has passed or usersmay not even attempt to locate a relevant application due to the hurdlesinvolved. Further, once an application is identified, permissions forthat application can be difficult to set or update. Yet further,existing computing systems fail to coordinate among applications,particularly in artificial reality systems where multiple applicationmay provide crowded or even overlapping output, making navigating andworking in the artificial reality environment difficult.

The artificial reality application system and processes described hereinare expected to alleviate these deficiencies in the prior art. Byproviding context-based, automatic download, suggestions, and executionfor applications, the disclosed artificial reality application system isable to provide timely and relevant applications, without the need toresearch applications for a given context or for interacting withconfusing and complicated application “stores.” In addition, by divingapplications into components that are download as needed, applicationscan be executed at need, much more quickly than in existing systems.Further, by provisioning permissions both through automatic inferencesand with a streamlined manual interface, users have faster and easiercontrol of application permissions. In addition, by implementingcontext-based ranking to coordinate among applications, multipleapplications configured to write to the same anchor or artificialreality environment area are limited, avoiding overcrowding andproviding more relevant and timely information and interfaces. Thesystems and processes described herein operate in the technical fieldfor application management in an artificial reality environment and, assuch, are clearly rooted in computer technologies. These systems andprocesses provide new application interaction and control models, whichare not analogs to exiting systems or know techniques.

Several implementations are discussed below in more detail in referenceto the figures. FIG. 1 is a block diagram illustrating an overview ofdevices on which some implementations of the disclosed technology canoperate. The devices can comprise hardware components of a computingsystem 100 that can provide automated, context-based applicationssuggestions, permissions controls, and orchestration. In variousimplementations, computing system 100 can include a single computingdevice 103 or multiple computing devices (e.g., computing device 101,computing device 102, and computing device 103) that communicate overwired or wireless channels to distribute processing and share inputdata. In some implementations, computing system 100 can include astand-alone headset capable of providing a computer created or augmentedexperience for a user without the need for external processing orsensors. In other implementations, computing system 100 can includemultiple computing devices such as a headset and a core processingcomponent (such as a console, mobile device, or server system) wheresome processing operations are performed on the headset and others areoffloaded to the core processing component. Example headsets aredescribed below in relation to FIGS. 2A and 2B. In some implementations,position and environment data can be gathered only by sensorsincorporated in the headset device, while in other implementations oneor more of the non-headset computing devices can include sensorcomponents that can track environment or position data.

Computing system 100 can include one or more processor(s) 110 (e.g.,central processing units (CPUs), graphical processing units (GPUs),holographic processing units (HPUs), etc.) Processors 110 can be asingle processing unit or multiple processing units in a device ordistributed across multiple devices (e.g., distributed across two ormore of computing devices 101-103).

Computing system 100 can include one or more input devices 120 thatprovide input to the processors 110, notifying them of actions. Theactions can be mediated by a hardware controller that interprets thesignals received from the input device and communicates the informationto the processors 110 using a communication protocol. Each input device120 can include, for example, a mouse, a keyboard, a touchscreen, atouchpad, a wearable input device (e.g., a haptics glove, a bracelet, aring, an earring, a necklace, a watch, etc.), a camera (or otherlight-based input device, e.g., an infrared sensor), a microphone, orother user input devices.

Processors 110 can be coupled to other hardware devices, for example,with the use of an internal or external bus, such as a PCI bus, SCSIbus, or wireless connection. The processors 110 can communicate with ahardware controller for devices, such as for a display 130. Display 130can be used to display text and graphics. In some implementations,display 130 includes the input device as part of the display, such aswhen the input device is a touchscreen or is equipped with an eyedirection monitoring system. In some implementations, the display isseparate from the input device. Examples of display devices are: an LCDdisplay screen, an LED display screen, a projected, holographic, oraugmented reality display (such as a heads-up display device or ahead-mounted device), and so on. Other I/O devices 140 can also becoupled to the processor, such as a network chip or card, video chip orcard, audio chip or card, USB, firewire or other external device,camera, printer, speakers, CD-ROM drive, DVD drive, disk drive, etc.

In some implementations, input from the I/O devices 140, such ascameras, depth sensors, IMU sensor, GPS units, LiDAR or othertime-of-flights sensors, etc. can be used by the computing system 100 toidentify and map the physical environment of the user while tracking theuser's location within that environment. This simultaneous localizationand mapping (SLAM) system can generate maps (e.g., topologies, girds,etc.) for an area (which may be a room, building, outdoor space, etc.)and/or obtain maps previously generated by computing system 100 oranother computing system that had mapped the area. The SLAM system cantrack the user within the area based on factors such as GPS data,matching identified objects and structures to mapped objects andstructures, monitoring acceleration and other position changes, etc.

Computing system 100 can include a communication device capable ofcommunicating wirelessly or wire-based with other local computingdevices or a network node. The communication device can communicate withanother device or a server through a network using, for example, TCP/IPprotocols. Computing system 100 can utilize the communication device todistribute operations across multiple network devices.

The processors 110 can have access to a memory 150, which can becontained on one of the computing devices of computing system 100 or canbe distributed across of the multiple computing devices of computingsystem 100 or other external devices. A memory includes one or morehardware devices for volatile or non-volatile storage, and can includeboth read-only and writable memory. For example, a memory can includeone or more of random access memory (RAM), various caches, CPUregisters, read-only memory (ROM), and writable non-volatile memory,such as flash memory, hard drives, floppy disks, CDs, DVDs, magneticstorage devices, tape drives, and so forth. A memory is not apropagating signal divorced from underlying hardware; a memory is thusnon-transitory. Memory 150 can include program memory 160 that storesprograms and software, such as an operating system 162, artificialreality application system 164, and other application programs 166.Memory 150 can also include data memory 170 that can include contextfactors, applications recommendation engine, permission setting,application activation settings, configuration data, settings, userinterfaces, user options or preferences, etc., which can be provided tothe program memory 160 or any element of the computing system 100.

Some implementations can be operational with numerous other computingsystem environments or configurations. Examples of computing systems,environments, and/or configurations that may be suitable for use withthe technology include, but are not limited to, XR headsets, personalcomputers, server computers, handheld or laptop devices, cellulartelephones, wearable electronics, gaming consoles, tablet devices,multiprocessor systems, microprocessor-based systems, set-top boxes,programmable consumer electronics, network PCs, minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, or the like.

FIG. 2A is a wire diagram of a virtual reality head-mounted display(HMD) 200, in accordance with some embodiments. The HMD 200 includes afront rigid body 205 and a band 210. The front rigid body 205 includesone or more electronic display elements of an electronic display 245, aninertial motion unit (IMU) 215, one or more position sensors 220,locators 225, and one or more compute units 230. The position sensors220, the IMU 215, and compute units 230 may be internal to the HMD 200and may not be visible to the user. In various implementations, the IMU215, position sensors 220, and locators 225 can track movement andlocation of the HMD 200 in the real world and in a virtual environmentin three degrees of freedom (3DoF) or six degrees of freedom (6DoF). Forexample, the locators 225 can emit infrared light beams which createlight points on real objects around the HMD 200. As another example, theIMU 215 can include e.g., one or more accelerometers, gyroscopes,magnetometers, other non-camera-based position, force, or orientationsensors, or combinations thereof. One or more cameras (not shown)integrated with the HMD 200 can detect the light points. Compute units230 in the HMD 200 can use the detected light points to extrapolateposition and movement of the HMD 200 as well as to identify the shapeand position of the real objects surrounding the HMD 200.

The electronic display 245 can be integrated with the front rigid body205 and can provide image light to a user as dictated by the computeunits 230. In various embodiments, the electronic display 245 can be asingle electronic display or multiple electronic displays (e.g., adisplay for each user eye). Examples of the electronic display 245include: a liquid crystal display (LCD), an organic light-emitting diode(OLED) display, an active-matrix organic light-emitting diode display(AMOLED), a display including one or more quantum dot light-emittingdiode (QOLED) sub-pixels, a projector unit (e.g., microLED, LASER,etc.), some other display, or some combination thereof.

In some implementations, the HMD 200 can be coupled to a core processingcomponent such as a personal computer (PC) (not shown) and/or one ormore external sensors (not shown). The external sensors can monitor theHMD 200 (e.g., via light emitted from the HMD 200) which the PC can use,in combination with output from the IMU 215 and position sensors 220, todetermine the location and movement of the HMD 200.

FIG. 2B is a wire diagram of a mixed reality HMD system 250 whichincludes a mixed reality HMD 252 and a core processing component 254.The mixed reality HMD 252 and the core processing component 254 cancommunicate via a wireless connection (e.g., a 60 GHz link) as indicatedby link 256. In other implementations, the mixed reality system 250includes a headset only, without an external compute device or includesother wired or wireless connections between the mixed reality HMD 252and the core processing component 254. The mixed reality HMD 252includes a pass-through display 258 and a frame 260. The frame 260 canhouse various electronic components (not shown) such as light projectors(e.g., LASERs, LEDs, etc.), cameras, eye-tracking sensors, MEMScomponents, networking components, etc.

The projectors can be coupled to the pass-through display 258, e.g., viaoptical elements, to display media to a user. The optical elements caninclude one or more waveguide assemblies, reflectors, lenses, mirrors,collimators, gratings, etc., for directing light from the projectors toa user's eye. Image data can be transmitted from the core processingcomponent 254 via link 256 to HMD 252. Controllers in the HMD 252 canconvert the image data into light pulses from the projectors, which canbe transmitted via the optical elements as output light to the user'seye. The output light can mix with light that passes through the display258, allowing the output light to present virtual objects that appear asif they exist in the real world.

Similarly to the HMD 200, the HMD system 250 can also include motion andposition tracking units, cameras, light sources, etc., which allow theHMD system 250 to, e.g., track itself in 3DoF or 6DoF, track portions ofthe user (e.g., hands, feet, head, or other body parts), map virtualobjects to appear as stationary as the HMD 252 moves, and have virtualobjects react to gestures and other real-world objects.

FIG. 2C illustrates controllers 270, which, in some implementations, auser can hold in one or both hands to interact with an artificialreality environment presented by the HMD 200 and/or HMD 250. Thecontrollers 270 can be in communication with the HMDs, either directlyor via an external device (e.g., core processing component 254). Thecontrollers can have their own IMU units, position sensors, and/or canemit further light points. The HMD 200 or 250, external sensors, orsensors in the controllers can track these controller light points todetermine the controller positions and/or orientations (e.g., to trackthe controllers in 3DoF or 6DoF). The compute units 230 in the HMD 200or the core processing component 254 can use this tracking, incombination with IMU and position output, to monitor hand positions andmotions of the user. The controllers can also include various buttons(e.g., buttons 272A-F) and/or joysticks (e.g., joysticks 274A-B), whicha user can actuate to provide input and interact with objects.

In various implementations, the HMD 200 or 250 can also includeadditional subsystems, such as an eye tracking unit, an audio system,various network components, etc. To monitor indications of userinteractions and intentions. For example, in some implementations,instead of or in addition to controllers, one or more cameras includedin the HMD 200 or 250, or from external cameras, can monitor thepositions and poses of the user's hands to determine gestures and otherhand and body motions.

FIG. 3 is a block diagram illustrating an overview of an environment 300in which some implementations of the disclosed technology can operate.Environment 300 can include one or more client computing devices 305A-D,examples of which can include computing system 100. In someimplementations, some of the client computing devices (e.g., clientcomputing device 305B) can be the HMD 200 or the HMD system 250. Clientcomputing devices 305 can operate in a networked environment usinglogical connections through network 330 to one or more remote computers,such as a server computing device.

In some implementations, server 310 can be an edge server which receivesclient requests and coordinates fulfillment of those requests throughother servers, such as servers 320A-C. Server computing devices 310 and320 can comprise computing systems, such as computing system 100. Thougheach server computing device 310 and 320 is displayed logically as asingle server, server computing devices can each be a distributedcomputing environment encompassing multiple computing devices located atthe same or at geographically disparate physical locations.

Client computing devices 305 and server computing devices 310 and 320can each act as a server or client to other server/client device(s).Server 310 can connect to a database 315. Servers 320A-C can eachconnect to a corresponding database 325A-C. As discussed above, eachserver 310 or 320 can correspond to a group of servers, and each ofthese servers can share a database or can have their own database.Though databases 315 and 325 are displayed logically as single units,databases 315 and 325 can each be a distributed computing environmentencompassing multiple computing devices, can be located within theircorresponding server, or can be located at the same or at geographicallydisparate physical locations.

Network 330 can be a local area network (LAN), a wide area network(WAN), a mesh network, a hybrid network, or other wired or wirelessnetworks. Network 330 may be the Internet or some other public orprivate network. Client computing devices 305 can be connected tonetwork 330 through a network interface, such as by wired or wirelesscommunication. While the connections between server 310 and servers 320are shown as separate connections, these connections can be any kind oflocal, wide area, wired, or wireless network, including network 330 or aseparate public or private network.

In some implementations, servers 310 and 320 can be used as part of asocial network. The social network can maintain a social graph andperform various actions based on the social graph. A social graph caninclude a set of nodes (representing social networking system objects,also known as social objects) interconnected by edges (representinginteractions, activity, or relatedness). A social networking systemobject can be a social networking system user, nonperson entity, contentitem, group, social networking system page, location, application,subject, concept representation or other social networking systemobject, e.g., a movie, a band, a book, etc. Content items can be anydigital data such as text, images, audio, video, links, webpages,minutia (e.g., indicia provided from a client device such as emotionindicators, status text snippets, location indictors, etc.), or othermulti-media, hi various implementations, content items can be socialnetwork items or parts of social network items, such as posts, likes,mentions, news items, events, shares, comments, messages, othernotifications, etc. Subjects and concepts, in the context of a socialgraph, comprise nodes that represent any person, place, thing, or idea.

A social networking system can enable a user to enter and displayinformation related to the user's interests, age date of birth, location(e.g., longitude/latitude, country, region, city, etc.), educationinformation, life stage, relationship status, name, a model of devicestypically used, languages identified as ones the user is facile with,occupation, contact information, or other demographic or biographicalinformation in the user's profile. Any such information can berepresented, in various implementations, by a node or edge between nodesin the social graph. A social networking system can enable a user toupload or create pictures, videos, documents, songs, or other contentitems, and can enable a user to create and schedule events. Contentitems can be represented, in various implementations, by a node or edgebetween nodes in the social graph.

A social networking system can enable a user to perform uploads orcreate content items, interact with content items or other users,express an interest or opinion, or perform other actions. A socialnetworking system can provide various means to interact with non-userobjects within the social networking system. Actions can be represented,in various implementations, by a node or edge between nodes in thesocial graph. For example, a user can form or join groups, or become afan of a page or entity within the social networking system. Inaddition, a user can create, download, view, upload, link to, tag, edit,or play a social networking system object. A user can interact withsocial networking system objects outside of the context of the socialnetworking system. For example, an article on a news web site might havea “like” button that users can click. In each of these instances, theinteraction between the user and the object can be represented by anedge in the social graph connecting the node of the user to the node ofthe object. As another example, a user can use location detectionfunctionality (such as a GPS receiver on a mobile device) to “check in”to a particular location, and an edge can connect the user's node withthe location's node in the social graph.

A social networking system can provide a variety of communicationchannels to users. For example, a social networking system can enable auser to email, instant message, or text/SMS message, one or more otherusers. It can enable a user to post a message to the user's wall orprofile or another user's wall or profile. It can enable a user to posta message to a group or a fan page. It can enable a user to comment onan image, wall post or other content item created or uploaded by theuser or another user. And it can allow users to interact (via theirpersonalized avatar) with objects or other avatars in a virtualenvironment, etc. In some embodiments, a user can post a status messageto the user's profile indicating a current event, state of mind,thought, feeling, activity, or any other present-time relevantcommunication. A social networking system can enable users tocommunicate both within, and external to, the social networking system.For example, a first user can send a second user a message within thesocial networking system, an email through the social networking system,an email external to but originating from the social networking system,an instant message within the social networking system, an instantmessage external to but originating from the social networking system,provide voice or video messaging between users, or provide a virtualenvironment were users can communicate and interact via avatars or otherdigital representations of themselves. Further, a first user can commenton the profile page of a second user, or can comment on objectsassociated with a second user, e.g., content items uploaded by thesecond user.

Social networking systems enable users to associate themselves andestablish connections with other users of the social networking system.When two users (e.g., social graph nodes) explicitly establish a socialconnection in the social networking system, they become “friends” (or,“connections”) within the context of the social networking system. Forexample, a friend request from a “John Doe” to a “Jane Smith,” which isaccepted by “Jane Smith,” is a social connection. The social connectioncan be an edge in the social graph. Being friends or being within athreshold number of friend edges on the social graph can allow usersaccess to more information about each other than would otherwise beavailable to unconnected users. For example, being friends can allow auser to view another user's profile, to see another user's friends, orto view pictures of another user. Likewise, becoming friends within asocial networking system can allow a user greater access to communicatewith another user, e.g., by email (internal and external to the socialnetworking system), instant message, text message, phone, or any othercommunicative interface. Being friends can allow a user access to view,comment on, download, endorse or otherwise interact with another user'suploaded content items. Establishing connections, accessing userinformation, communicating, and interacting within the context of thesocial networking system can be represented by an edge between the nodesrepresenting two social networking system users.

In addition to explicitly establishing a connection in the socialnetworking system, users with common characteristics can be consideredconnected (such as a soft or implicit connection) for the purposes ofdetermining social context for use in determining the topic ofcommunications. In some embodiments, users who belong to a commonnetwork are considered connected. For example, users who attend a commonschool, work for a common company, or belong to a common socialnetworking system group can be considered connected. In someembodiments, users with common biographical characteristics areconsidered connected. For example, the geographic region users were bornin or live in, the age of users, the gender of users and therelationship status of users can be used to determine whether users areconnected. In some embodiments, users with common interests areconsidered connected. For example, users' movie preferences, musicpreferences, political views, religious views, or any other interest canbe used to determine whether users are connected. In some embodiments,users who have taken a common action within the social networking systemare considered connected. For example, users who endorse or recommend acommon object, who comment on a common content item, or who RSVP to acommon event can be considered connected. A social networking system canutilize a social graph to determine users who are connected with or aresimilar to a particular user in order to determine or evaluate thesocial context between the users. The social networking system canutilize such social context and common attributes to facilitate contentdistribution systems and content caching systems to predictably selectcontent items for caching in cache appliances associated with specificsocial network accounts.

FIG. 4 is a block diagram illustrating components 400 which, in someimplementations, can be used in a system employing the disclosedtechnology. Components 400 can be included in one device of computingsystem 100 or can be distributed across multiple of the devices ofcomputing system 100. The components 400 include hardware 410, mediator420, and specialized components 430. As discussed above, a systemimplementing the disclosed technology can use various hardware includingprocessing units 412, working memory 414, input and output devices 416(e.g., cameras, displays, IMU units, network connections, etc.), andstorage memory 418. In various implementations, storage memory 418 canbe one or more of: local devices, interfaces to remote storage devices,or combinations thereof. For example, storage memory 418 can be one ormore hard drives or flash drives accessible through a system bus or canbe a cloud storage provider (such as in storage 315 or 325) or othernetwork storage accessible via one or more communications networks. Invarious implementations, components 400 can be implemented in a clientcomputing device such as client computing devices 305 or on a servercomputing device, such as server computing device 310 or 320.

Mediator 420 can include components which mediate resources betweenhardware 410 and specialized components 430. For example, mediator 420can include an operating system, services, drivers, a basic input outputsystem (BIOS), controller circuits, or other hardware or softwaresystems.

Specialized components 430 can include software or hardware configuredto perform operations for suggesting and controlling applications in anartificial reality environment. Specialized components 430 can includeanchor point detector 434, context detector 436, application suggestionmodule 438, permissions module 440, progressive download module 442,application ranking module 444, and components and APIs which can beused for providing user interfaces, transferring data, and controllingthe specialized components, such as interfaces 432. In someimplementations, components 400 can be in a computing system that isdistributed across multiple computing devices or can be an interface toa server-based application executing one or more of specializedcomponents 430. Although depicted as separate components, specializedcomponents 430 may be logical or other nonphysical differentiations offunctions and/or may be submodules or code-blocks of one or moreapplications.

Anchor point detector 434 can identify artificial reality environmentanchor points. Anchor points can be individual points, a 2D surface, ora 3D volume. In some cases, anchor points can correspond to anidentified object, surface, type of object, or type surface. Additionaldetails on identifying artificial reality environment anchor points areprovided below in relation to block 502 of FIG. 5 .

Context detector 436 can determine a current context for an XR device.The current context can include data determined by sensors of the XRdevice (either directly or via further processing such as with trainedmachine learning models, heuristics, etc.), retrieved from third partysources (e.g., news feeds, social media platforms, weather services,etc.), or local data (e.g., logs of user events, communications,activities, etc.) The context can include features for a user context(e.g., user activity/posture, location, social graph connections tonearby users, calendar events for the user, known user routines, whetherthe user in a conversation, where user has been looking, user setpreferences, etc.) and/or for an artificial reality environment context(e.g., surfaces and objects in the artificial reality environment,current time, scene tags such as noisy, crowded, etc.) Additionaldetails on identifying a context are provided below in relation to block504 of FIG. 5 and block 906 of FIG. 9 .

Application suggestion module 438 can identify one or more applicationsthat match the anchor(s) identified by anchor point detector 434 and/orthat match the context identified at context detector 436. This matchingcan be by one or more of: A) comparing a set of anchor point typesdefined for an application to types of identified anchor points, B)comparing a set of context features mapped to an application to currentcontext features, and/or C) applying a machine learning model trained todetermine a match score between application features and contextfeatures and/or anchor points. Once matches are made, additional rulescan be applied, such as limiting whether multiple applications of thesame type are in the top matches. The resulting matching applicationscan be suggested to the user. Additional details on providingcontext-specific application suggestions are provided below in relationto blocks 506 and 508 of FIG. 5 .

Permissions module 440 can identify that a user has provided an actionin relation to one or more of the applications suggested by applicationsuggestion module 438 and, in response, can set permissions for theauthorized application(s), such as permissions to write augments into anew space, provide notifications, access input signals, receive contextfeatures, perform authentications, share or message with other users orwrite into a shared XR space, exchange objects or other data with otherauthorized applications, etc. Permissions module 440 can also receiveexplicit or implied permissions changes from a user (e.g., based onwhether the user has interacted with a threshold amount of augmentsprovided by an application or application type) and, in response, canremove application permissions. Additional details on setting andupdating application permissions are provided below in relation to block512 of FIG. 5 , and FIGS. 7 and 8 .

Progressive download module 442 can identify a trigger for applicationaugment creation or other output, where the application is not fullyresident on the XR device and can determine a priority order forapplication component downloads, based on the triggered aspects of theapplication. Progressive download module 442 can then begin download ofthose application components according to the priority order. Additionaldetails on progressive download of application components are providedbelow in relation to FIG. 6 .

Application ranking module 444 can identify when multiple applicationsare simultaneously authorized to execute in an artificial realityenvironment, and in some cases on the same anchor points and can employa ranking system to limit the amount of augments that can be anchored toa particular surface, object, within a physical space, and/or within anarea in the user's field of view. Ranking module 444 can define rankingsamong the applications that can write to a given anchor or area, wherethe rankings can account for a current context from context detector436. With the application rankings, and in some cases additional rulesfor allowing application output, ranking module 444 can select thresholdamounts of output from highest ranking applications for output toanchors and spaces. Additional details on ranking applications forprioritized output are provided below in relation to FIG. 9 .

Those skilled in the art will appreciate that the components illustratedin FIGS. 1-4 described above, and in each of the flow diagrams discussedbelow, may be altered in a variety of ways. For example, the order ofthe logic may be rearranged, substeps may be performed in parallel,illustrated logic may be omitted, other logic may be included, etc. Insome implementations, one or more of the components described above canexecute one or more of the processes described below.

FIG. 5 is a flow diagram illustrating a process 500 used in someimplementations of the present technology for providing context-basedapplication suggestions and recognizing a user action as anauthorization for a suggested application. Process 500 can be performedto suggest one or more “ambient” applications, which appear to the useras applications that are always on without having to manually find,download, and install, the application. In some implementations, process500 can be performed on an XR device, e.g., as a user moves about anartificial reality environment. In other implementations, process 500can be performed on a server system supporting the XR device, e.g., withinput from the XR device specifying sensor data such as color and depthimages, SLAM data, IMU data, etc. In some cases, process 500 can beperformed periodically, e.g., every second or fraction of a second tosuggest applications or can be performed in response to triggers such asa certain amount of movement of the XR device or an identified change inobjects in the XR device's artificial reality environment.

At block 502, process 500 can identify artificial reality environmentanchor points. Anchor points can be individual points, a 2D surface, ora 3D volume. In some cases, anchor points can correspond to anidentified object, surface, type of object, or type surface. Forexample, if an artificial reality application system identifies that auser is walking down a grocery store isle with food items, recognizedfood items can become anchor points. As another example, the artificialreality application system can identify a surface type by determining aflat plane of a particular size and orientation, such as identifying awall surface by determining a flat plane that is vertical and at leasttwelve square feet.

At block 504, process 500 can determine a current XR context. The XRcontext can include any data determined by sensors of the XR device(either directly or via further processing such as with trained machinelearning models, heuristics, etc.), retrieved from third party sources(e.g., news feeds, social media platforms, weather services, etc.), orlocal data (e.g., logs of user events, communications, activities, etc.)For example, the current XR context can include one or more of:identified objects and/or surfaces around the user, current locationdata for the user (e.g., GPS data and/or SLAM data), user state(emotion, posture/gestures, gaze direction), relationship to other usersin the area (e.g., their presence, their actions, their relationship tothe current user on a social graph), known events or calendar items forthe user, recent messaging activity of the user, user preferences,current time or date, current lighting, weather or other environmentconditions, identified sounds in the environment, etc.

At block 506, process 500 can identify one or more applications thatmatch the anchor(s) identified at block 502 and/or that match the XRcontext identified at block 506. In various cases, applications to bematched with the XR context and/or anchor point can be locally installedon the XR device, can be from an “app store,” can have been indicated byanother user (e.g., shared in a chat session or otherwise sent to thecurrent user), can have been tagged to the user's current location(e.g., an owner of an establishment can provide an application for userin that residence), etc.

An application can specify a set of anchor point types for which it cansupply content and the application can match an anchor point when thetype of the anchor point is in the set of specified anchor points forthat application. In some implementations, particular sets of contextfeatures can be mapped to an application to determine a match between acontext and the application. For example, an application creator oradministrator can register the application for a set of contextualfeatures such as the object types or locations for which the applicationis configured to provide output, context features with which other usershave used the application, or contexts for which users have recommendedthe application. In other implementations, a machine learning model canbe trained to determine a match score between features of a context(e.g., provided as values in a sparse vector) and a specifiedapplication or type defined for the application (e.g., transportationmapping application, photo gallery application, etc.) Such a machinelearning model, (e.g., a neutral network), can be trained on trainingitems that are created by matching examples of a user manually selectingan application to use with a current context. For example, when a useris in a context of walking down a city street and the user opens the mapapplication, this context/application pair can be provided as a positivetraining item. Other installed application that were not selected can bepaired with the context as negative training items. In some cases, amatch occurs only when there is a match between the application and boththe XR context and the anchor point. In other cases, a match occurs whenthe application matches to either the anchor point or context. In yetfurther cases, process 500 may only determine whether one of the anchorpoint or XR context is a match with applications. In some cases, a matchcan include a match score—i.e., how well the context and/or anchor pointalign with the specified set of anchor points and/or context featuresfor the application. For example, the machine learning model trained todetermine a match can produce the match score.

At block 508, process 500 can provide application suggestions for one ormore of the matches that have the top match scores. In someimplementations, suggestions can be provided as overlays in anartificial reality environment, e.g., as a list of suggestedapplications positioned relative to the determined anchor point matchedto the suggested application. For example, if a user's field of viewincludes a particular kind of car identified as an anchor point and thematched application with the highest match score is an automobile salesapplication, an indication (e.g., icon) of the automobile salesapplication can be positioned next to the car. In variousimplementations, a number of application suggestions can be provided,such as one, two, or three; only applications with a match score above athreshold can be provided; and/or application suggestions can beprovided according to an amount of room determined for a suggestionarea. For example, an area next to an anchor point can be designated foraugments and suggestion can be made while this area is not full withother suggestions or with augments that previously authorizedapplications have written to that area. In another example, there may bea limit on the amount of the user's field of view that can be taken upby augments, preventing the user from being overwhelmed by augmentswritten into her environment.

In some cases, the applications can have assigned categories, and alimited amount of applications from a category (e.g., those with thehighest match scores in that category) are shown. For example, if thereare five matching applications—a mapping category application A with amatch score of 0.95, a special offer category application B with a matchscore of 0.83, a special offer category application C with a match scoreof 0.79, a mapping category application D with a match score of 0.72,and a game category application E with a match score of 0.71—where threeapplications can be suggested, the first mapping category application Acan be suggested due to its match score of 0.95, the first special offercategory application B can be suggested due to its match score of 0.83,the next two special offer category and mapping category applications Cand D can be skipped because an application from each of thesecategories was already selected, and the a game category application Ewith the match score of 0.71 can be suggested.

At block 510, process 500 can receive a user action to authorizeexecution of one or more of the applications suggested in block 508.Examples of such user actions include dragging the indication of theapplication out of the suggestion area, tapping the indication of thesuggested application, providing a voice command indicating thesuggested application, opening a dialog control to approve theapplication, etc.

At block 512, process 500 can set permissions for the application(s)authorized at block 510. Applications can have various permissions suchas to write augments into a new space, provide notifications (e.g., whenthe application is otherwise inactive), access input signals (e.g., froma XR device camera, microphone, etc.), receive context features (e.g.,user status, surrounding objects, third-party data, etc.), performauthentications (e.g., logging into other systems, accessing paymentplatforms, etc.), share or message with other users or write into ashared XR space, exchange objects or other data with other authorizedapplications, etc. The permissions set for an application can be astandard set of permissions for user-authorized applications orpermissions to provide output for the anchor point or anchor point typefrom block 502, when a threshold amount of context features from block504 (e.g., those that were the cause of the match at block 506) exist,or general permissions to perform a set of actions specified by theapplication (e.g., where the set of actions are presented to the userfor authorization as part of the user authorization action of block510).

At block 514, process 500 can allow the application authorized at block510 to show augments or provide other output according to thepermissions set at block 512. In some cases, the application can providethe augment or other output in relation to the user action from block510. For example, if the user action was to pull the indication of theapplication out of the suggestion area into her environment, an augmentcreated by the authorized application be placed where the user droppedthe indication of the application. In some cases, the application canprovide the augment or other output in relation to aspects of thematched context (from block 506) and/or anchor point (from block 502).For example, an augment created by the authorized application can at theanchor point (e.g., at a particular point, on a particular surface, in aparticular volume, etc.) and/or can be placed in relation to thelocation of objects or events that were matched (e.g., if the matchedcontext included identifying a particular object, the authorizedapplication can write to an augment that encapsulates that object). Insome cases, an authorized application may only have permissions toprovide output in certain circumstances which may not currently exist ormay not provide visual output at all, but feedback such as an animationor sound can be provided to signal to the user that her attempt toactivate the application was successful.

In some cases, when an application is triggered to provide output suchas at block 514, the application may not be fully resident on (i.e.,have all its components downloaded to) the XR device. However,applications can be divided into multiple components which can beprogressively downloaded to provide the output before the application isfully resident. This can be accomplished using the prioritizationprocess for progressive download discussed below in relation to FIG. 6 .

FIG. 6 is a flow diagram illustrating a process 600 used in someimplementations of the present technology for progressive download ofapplication components. In some implementations, process 600 can beperformed on a XR device. Process 600 can be performed in response toexecution of an application which is not fully resident on the XRdevice. For example, process 600 can be performed as a subprocess ofprocess 500, e.g., at block 514. Applications can be divided intocomponents (e.g., data source, instance, presenter, augments, visualelements, action scripts, etc.) and process 600 can download thenecessary components and hydrate content as needed. This allows theapplications to execute as needed without the user having to wait untilthe application is fully resident before being able to use parts of it.This also provides an “always on” feeling to applications, letting theuser not worry about whether an application is installed or even if it'slocal or remote. This can also save storage space, allowing unusedapplications or application components to be discarded when space islow, and re-downloaded as needed.

At block 602, process 600 can identify a trigger for application augmentcreation or other output, where the application is not fully resident onthe XR device. While any event can trigger an application output,examples of such triggers include the XR device recognizing an objectfor which the application has registered, a timer expiring, a useraction indicating the application, etc.

At block 604, process 600 can determine a priority order for applicationcomponent downloads, based on the triggered aspects of the application,and begin the download of those application components. The triggeredaspects of the application are those that will be used to provide theoutput in response to the trigger identified at block 602. For example,if certain scripts or visual elements are needed to create content foran augment that respond to the trigger, these components can beprioritized ahead of other components that may not be needed to respondto the trigger. In some cases, visual elements can be prioritized aheadof those that may respond to further actions of the user. For example,an augment can be created with its visual elements, with the assumptionthat a user may not immediately interact with the augment, allowing thesystem time to download the active programming elements in the interimbetween when the augment is displayed and when the user beginsinteracting with it. In some cases, some of the visual elements can beinitially downloaded at a lower resolution and displayed quickly, andthen replaced later as higher resolution versions are downloaded. Insome instances, application components can be groups into batchesaccording to when they are expected to be needed. For example, aninitial set of visual components can be put in a first batch andprogramming elements can be put in a later batch. Each batch can bedownloaded together, with the next batch starting when the previous oneis complete.

FIG. 7 is a flow diagram illustrating a process 700 used in someimplementations of the present technology for controlling applicationpermissions via an application manager. In various implementations,process 700 can be performed on an XR device or on a remote supportingsystem (e.g., server) that is in control of application permissions forthe XR device. Process 700 can be triggered by various user actions toaccess application permission controls such as by activating a UIcontrol, speaking a command, performing a gesture, etc. In some cases,the user action (e.g., by opening a menu and selecting an applicationmanager control) can be mapped to access a general application managerwhile other actions (e.g., performing a long-pinch gesture) on anaugmented created by an particular application or a displayedrepresentation of the particular application can be mapped to access asub-section of the application manager for the particular application.

At block 702, process 700 can cause the application manager (orsub-section thereof corresponding to an indicated application) to bedisplayed. The application manager can include controls allowing a userto make specific selections as to what permissions the listedapplications are assigned. In some cases, the permissions control can bea single enabled/disabled button, which when switched to disabledprevents an application from providing any output. An example of such anapplication manager is provided in FIG. 12 . In some implementations,the permissions controls can include more fine-grained controls overindividual permissions such as to write augments into a new space,provide notifications (e.g., when the application is otherwiseinactive), access input signals (e.g., from a XR device camera,microphone, etc.), receive context features (e.g., user status,surrounding objects, third-party data, etc.), perform authentications(e.g., logging into other systems, accessing payment platforms, etc.),share or message with other users or write into a shared XR space,exchange objects or other data with other authorized applications, etc.In some cases, the application manager can include both, where there isa general enable/disable control for each application and a way to drilldown in the selections to set individual permissions.

As discussed above, any block can be removed or rearranged in variousimplementations. However, block 704 is shown in dashed lines to indicatethere are specific instances where block 704 is skipped. At block 704,process 700 can receive user selections of search parameters or filtersfor the applications listed in the displayed application manager. Forexample, the applications can be tagged with various meta-data such asapplication types, keywords, user rankings/reviews, when the applicationlast provided output to the current user, a frequency of output by thisapplication, types of output provided by the application, types ofobjects or events the application has registered to receive, etc.Through various controls and selections, a user can indicate which ofthese meta-data to search for, sort by, and/or filter the list ofapplications by.

At block 706, process 700 can receive one or more permissions selectionsfor listed applications. These permissions selections can be throughactivation of the controls displayed at block 702, such as toenable/disable an application or to set particular permission for anapplication. In some implementations, the permissions selections canregister or de-register an application for objects and events theapplication can control or be made aware of. For example, theapplication manager can provide a list of such objects or events that anapplication has registered for, and the user can provide selections toremove the registrations or provide new ones. In some cases, thepermissions selections can be accompanied by rules or that define whenthe selection is to take effect and/or when the permissions selectionsexpire. For example, users can set a mute timer or trigger for adisabled application, allowing the disabled application to be re-enabledwhen the timer expires or the event occurs. As a more specific example,a rule can be setup to disable an application in a particular location,when an event occurs on the user's calendar, or when the XR devicedetermines the user is engaged in a live conversation, and the rule canspecify to re-enable the application when the user is no longer at thelocation, the calendar event ends, or the live conversation ends.Following the selections, process 700 can set permissions forapplications according to the received permissions selections. Forexample, upon deactivation of an application, all augments that werecreated by that application can be closed and the application may longerhave permissions to create augments in the artificial realityenvironment. In some cases, a deactivated application may beuninstalled, either immediately or as storage space on the XR device isneeded.

FIG. 8 is a flow diagram illustrating a process 800 used in someimplementations of the present technology for controlling applicationpermissions in response to a context. In various implementations,process 800 can be performed on an XR device or on a remote supportingsystem (e.g., server) that is in control of application permissions forthe XR device. Process 800 can be executed by a control system of the XRdevice, e.g., upon startup of the XR device, periodically (e.g., every0.1-3 seconds), or when certain events occur such as an identifiedchange in a current context (e.g., when the XR device has determined ithas moved a threshold amount, when a new object enters the artificialreality environment, when new third-party data comes in, etc.)

At block 802, process 800 can identify a permissions trigger. In somecases, the permissions trigger can be one or more events or othercontextual factors (e.g., recognized user state, recognized object inthe artificial reality environment, condition identified in third-partydata, etc.) that have been mapped to a permissions change. For example,application permissions can be set that cause the application to mute(i.e., pause providing output) when it's determined that a user is in aconversation, is driving, is at work, etc. In other cases, thepermissions trigger can be an identified user intent to disable or mutean application. Such an intent can be inferred from user actions such asthe user closing or not interacting with a threshold amount (e.g.,number, percentage, etc.) of augments generated by the applicationwithin a threshold time window (e.g., in the past day or week). Forexample, if an application produced ten augments in the past day, butthe user interacted with only two of them, which is less than a 40%threshold in the one day time window, then that application can bemuted. As another example, if the application produced 75 augments inthe past week, but the user interacted with only six of them, which isless than a 15% threshold in the one week time window, then thatapplication can be disabled. In some cases, user intents can beidentified for a type of application, such as by identifying if a userignored or closed augments from a type of application within a timewindow, even though the augments came from different applications ofthat type. In some implementations, when a user intent is identified,the intent can be confirmed with the user (e.g., through a dialog of “Doyou want to disable the MapStar application?” or “Do you want to disableall instant messaging applications?”)

At block 804, process 800 can set permissions mapped to the permissionstrigger, identified at block 802, for the associated application(s).Each permissions trigger can be mapped to a corresponding action, suchas muting or disabling an application, which can be implemented for theapplication (or set of applications in the type) corresponding to thepermissions trigger. In various implementations, the permissions changecan be for the application(s) generally or may only be made for acontext in which the permissions trigger occurs. For example, if thepermissions trigger is that a user has disable a threshold number ofnutrition suggestions while in a supermarket, and the permissions changeis to mute the application, the permissions change can be implemented sothat the nutrition suggestions only are muted in supermarkets but notother contexts, such as when the user is looking in her fridge.Following the permissions change, process 800 can end until its nextexecution.

FIG. 9 is a flow diagram illustrating a process 900 used in someimplementations of the present technology for prioritizing applicationoutput through a context-specific ranking. In various implementations,process 900 can be performed on an XR device or on a remote supportingsystem (e.g., server) that is in control of application output for theXR device. Process 900 can be executed by a control system of the XRdevice, e.g., upon identifying an event or object that multipleapplications have each registered to receive notification of and haverequested an augment space in relation to.

At block 902, process 900 can identify a limiting condition forapplication output. In some implementations, an XR device can beconfigured to limit the number of augments or area taken up by augments,either as a limit on augments within any give area of the user's fieldof view or as a limit on augments that can be attached to a particularobject or other anchor point. In various cases, different limits can beset for different types of objects (e.g., based on the objectsprominence in the user's field of view) or anchor points (e.g., based onthe anchor point type (point, surface, volume), size, or establishedlayout). For example, when three applications request an augmentanchored such that they would be overlapping or within a thresholddistance of one another in the user's field of view, process 900 canidentify this as a limiting condition. As another example, when twoapplications request an augment anchored to the same object, process 900can identify this as a limiting condition.

As discussed above, any block can be removed or rearranged in variousimplementations. However, block 904 is shown in dashed lines to indicatethere are specific instances where block 904 is skipped. At block 904,process 900 can apply heuristic rules for limiting application output.While a variety of such rules can be defined, examples include: rules tolimit how many applications of the same type can concurrently provideoutput (or output on the same object or within a threshold distance ofone another), rules to specify types or configurations of augments thatcan be attached to certain types of object, user specified preferenceson application output limits, etc.

At block 906, process 900 can define a context-specific ranking amongthe applications that were involved in the identification of thelimiting condition at block 902. The context specific ranking can becomputed by a machine learning model trained to match an application toa context, where features of the context are provided to the model(e.g., as a sparse vector) along with an identification of theapplication or tags describing the application (e.g., application type,types of application output, application uses, etc.) and the modelproduces a score defining how well the application matches the context.Such a machine learning model (e.g., a neutral network) can be trainedon training items that are created by matching examples of a usermanually selecting an application or interacting with a created augment(e.g., performing a gesture in relation to an augment, having the user'sgaze rest on the augment for above a threshold time) to use with acurrent context. For example, when a user is in a context of walkingdown a city street and the user opens the map application, thiscontext/application pair can be provided as a positive training item.Other installed applications that were not selected can be paired withthe context as a negative training item. As another example, when a useris in a context and an application creates and augment that the userthen interacts with (e.g., using a grab gestures to look at it frommultiple angles,) this pair of the context and creating application canbe provided as a positive training item.

In various implementations, the context can include features for a userstatus, such as user movement/posture, location, social graphconnections to nearby users, calendar events for the user, known userroutines, whether the user in a conversation, where user has beenlooking, user history with applications (e.g., user interaction or focustime above a threshold time with augments from an application), user-setpreferences, etc. The context can also include data determined bysensors of the XR device, either directly or via further processing suchas with trained machine learning models, heuristics, etc. (e.g.,surfaces and objects in the artificial reality environment, currenttime, scene tags such as noisy, crowded, etc.) The context can alsoinclude data retrieved from third party sources (e.g., news feeds,social media platforms, weather services, etc.) or local data (e.g.,logs of user events, communications, activities, etc.)

At block 908, process 900 can select a threshold amount of output fromthe application(s) ranked highest at block 908. In some implementations,the threshold amount of output can be based on an amount of outputallowed by the limiting condition identified at block 902. For example,there can be a threshold number of augments that can be attached to anobject or there can be a designated area or surface that applicationscan output to, and output can be selected from the highest rankingapplications until the maximum number is reached or that area is full.As additional examples, the threshold amount can be an amount of theuser's field of view that augments can take up or a maximum density ofaugments that can be put in a given portion of the user's field of view.In some cases, the selection of the highest ranking applications can bebased on the heuristics from block 904. For example, a rule can specifythat, for a given object, only a single augment from the same type ofapplication can be attached, and that the limiting condition can specifythat only two augments can be attached to the object. Thus, in thisexample, if the top two scoring applications are mapping applicationsand the third scoring application is a local history application, thetop scoring mapping application can attach an augment to the object andthe local history application will be given the second augment slot asthe second mapping application is precluded by the rule. Process 900 canrepeat as the context changes and additional limiting conditions areidentified.

FIG. 10 is a conceptual diagram illustrating an example 1000 of a user1001 receiving application suggestions (in frame 1002), peeling asuggestion to enable the application (in frame 1004), and viewingaugments from the enabled application (in frame 1006). In frame 1002,user 1001 is wearing XR device 1012, which has identified and anchorpoint and a context and selected applications to suggest, indications ofwhich are shown to the user 1001 at 1008. The user casts a virtual ray1010 at application indication 1014. In frame 1004, user 1001 movesvirtual ray 1010 to drag the indication 1014 out of the suggestion area1008 and into the artificial reality environment. This causesprogressive download of the components for the applicationscorresponding to indication 1014 and sets permissions for thisapplication to be able to create augments in the artificial realityenvironment. In frame 1006, the application exercises these permissionsto write augments 1016A-1016E into the artificial reality environment,which the user 1001 views via the XR device 1012.

FIGS. 11A-11C illustrate examples or the field of view provided by an XRdevice while receiving application suggestions, peeling a suggestion toenable the application, and viewing an augment from the enabledapplication. FIG. 11A is a conceptual diagram illustrating an example1100 of receiving application suggestions for a context. In example1100, the XR device has recognized that the user's gaze has lingered onan object identified 1102 as a transportation sign. The XR device hasadded a border around the recognized object 1102—signifying that this isthe anchor point for application suggestions and the context for thesuggestions the XR device is making. Based on this anchor point andcontext, the XR device has identified three applications that match, andhave suggested them in the application suggestion area 1104 proximatethe identified object 1102. These suggestions include applicationindications 1106, 1108, and 1110. FIG. 11B is a conceptual diagramillustrating an example 1140 of receiving authorization for a selectionof a suggested through a drag gesture. In example 1140, a user 1142 hasmade a pinch gesture to start a virtual ray 1144. The user 1142 directed(not shown) the virtual 1144 at the application indication 1106. Then,as indicated by arrow 1146, dragged the application indication 1106inside the border of object 1102. The XR device recognizes this as anaction to authorize the application indicated by 1106, causingprogressive download of the application's components and providingpermissions for the application to create an augment in relation toobject 1102. FIG. 11C is a conceptual diagram illustrating an example1170 of an authorized application generating an augment in relation to acontext. In example 1170, the authorized application has requested aspace 1172 as an augment locked to object 1102 and, based on theassigned application permissions, has been authorized to write into thatspace 1172. The authorized application thus writes content 1174— showingtransit options related to the content of the transit sign object 1102—into the space 1172.

FIG. 12 is a conceptual diagram illustrating an example 1200 of anapplication manager. In example 1200, a user has provided a command toaccess the application manager, e.g., through activation of a UI controlor voice command. In this example, the application manager has dividedthe set of applications installed on the XR device into threecategories: Transit 1202, Travel 1204, and Entertainment 1206.Applications have been put into these categories according to meta-datatags assigned to them by the application creators. The user can selectany of these categories as a filter for the list of applications toshow. In example 1200, the user has selected the Transit 1202 category.This shows the list 1208 of the installed transit applications. Each ofthe applications in the list is associated with a control (1210, 1212,and 1214), which can be selected or de-selected to enable to disable thecorresponding application. In example 1200, the user has de-selectedcontrol 1212, to disable it. This revokes the permissions for thatapplication to create any augments in the artificial realityenvironment. It also schedules the components of this application to bedeleted as storage space is required on the XR device.

Reference in this specification to “implementations” (e.g., “someimplementations,” “various implementations,” “one implementation,” “animplementation,” etc.) means that a particular feature, structure, orcharacteristic described in connection with the implementation isincluded in at least one implementation of the disclosure. Theappearances of these phrases in various places in the specification arenot necessarily all referring to the same implementation, nor areseparate or alternative implementations mutually exclusive of otherimplementations. Moreover, various features are described which may beexhibited by some implementations and not by others. Similarly, variousrequirements are described which may be requirements for someimplementations but not for other implementations.

A “machine learning model” (sometimes referred to as a model), as usedherein, refers to a construct that is trained using training data tomake predictions or provide probabilities for new data items, whether ornot the new data items were included in the training data. For example,training data for supervised learning can include items with variousparameters and an assigned classification. A new data item can haveparameters that a model can use to assign a classification to the newdata item. As another example, a model can be a probability distributionresulting from the analysis of training data, such as a likelihood of ann-gram occurring in a given language based on an analysis of a largecorpus from that language. Examples of models include: neural networks,support vector machines, decision trees, Parzen windows, Bayes,clustering, reinforcement learning, probability distributions, decisiontrees, decision tree forests, and others. Models can be configured forvarious situations, data types, sources, and output formats. In someimplementations, the model can be a neural network with multiple inputnodes. The input nodes can correspond to functions that receive inputand produce results. These results can be provided to one or more levelsof intermediate nodes that each produce further results based on acombination of lower level node results. A weighting factor can beapplied to the output of each node before the result is passed to thenext layer node. At a final layer, (“the output layer,”) one or morenodes can produce a value classifying the input. In someimplementations, such neural networks, known as deep neural networks,can have multiple layers of intermediate nodes with differentconfigurations, can be a combination of models that receive differentparts of the input and/or input from other parts of the deep neuralnetwork, or are convolutions or recurrent —partially using output fromprevious iterations of applying the model as further input to produceresults for the current input.

As used herein, being above a threshold means that a value for an itemunder comparison is above a specified other value, that an item undercomparison is among a certain specified number of items with the largestvalue, or that an item under comparison has a value within a specifiedtop percentage value. As used herein, being below a threshold means thata value for an item under comparison is below a specified other value,that an item under comparison is among a certain specified number ofitems with the smallest value, or that an item under comparison has avalue within a specified bottom percentage value. As used herein, beingwithin a threshold means that a value for an item under comparison isbetween two specified other values, that an item under comparison isamong a middle-specified number of items, or that an item undercomparison has a value within a middle-specified percentage range.Relative terms, such as high or unimportant, when not otherwise defined,can be understood as assigning a value and determining how that valuecompares to an established threshold. For example, the phrase “selectinga fast connection” can be understood to mean selecting a connection thathas a value assigned corresponding to its connection speed that is abovea threshold.

As used herein, the word “or” refers to any possible permutation of aset of items. For example, the phrase “A, B, or C” refers to at leastone of A, B, C, or any combination thereof, such as any of: A; B; C; Aand B; A and C; B and C; A, B, and C; or multiple of any item such as Aand A; B, B, and C; A, A, B, C, and C; etc.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Specific embodiments and implementations have been described herein forpurposes of illustration, but various modifications can be made withoutdeviating from the scope of the embodiments and implementations. Thespecific features and acts described above are disclosed as exampleforms of implementing the claims that follow. Accordingly, theembodiments and implementations are not limited except as by theappended claims.

Any patents, patent applications, and other references noted above areincorporated herein by reference. Aspects can be modified, if necessary,to employ the systems, functions, and concepts of the various referencesdescribed above to provide yet further implementations. If statements orsubject matter in a document incorporated by reference conflicts withstatements or subject matter of this application, then this applicationshall control.

1. A method for suggesting, authorizing, and controlling applicationoutput in an artificial reality (XR) device, the method comprising:identifying one or more artificial reality environment anchor points,which specify real-world locations, to which application output will beattached in an artificial reality environment; determining a pluralityof features of a current XR context, defining a) characteristics of auser and b) an automatically determined state of the real-world in avicinity of the user, the current XR context comprising one or more of:determinations based on sensor data gathered by the XR device, dataretrieved from a third party source, data local to the XR device, or anycombination thereof; providing suggestions for one or more applicationsthat match the current XR context and at least one anchor point of theone or more artificial reality environment anchor points, wherein eachparticular application is identified by: determining that a) a thresholdsubset of multiple features from the plurality of features of thecurrent XR context have been mapped to the particular application andthat b) the particular application is configured to provide output inrelation to the at least one anchor point; or applying a machinelearning model, trained to determine a match score, to multiple featuresof the current XR context and to a type specified for the particularapplication, and determining that a resulting match score is above athreshold; receiving a user action to authorize a selected applicationof the suggested one or more applications; and in response to the useraction: obtaining components of the selected application; and settingpermissions for the selected application that allow the selectedapplication to provide output, in the artificial reality environment,attached to the at least one anchor point.
 2. The method of claim 1,wherein each of the one or more anchor points corresponds to arespective particular real-world object identified by the XR device. 3.The method of claim 1, wherein the current XR context comprises: one ormore identified objects in the artificial reality environment, currentlocation data for the XR device, one or more aspects of a user stateand/or one or more relationships to one or more other users identifiedin the area of the XR device, and environment conditions.
 4. The methodof claim 1, wherein identifying the one or more applications isperformed by the determining that the threshold subset of features fromthe current XR context has been mapped to the particular application. 5.The method of claim 1, wherein identifying the one or more applicationsis performed by the applying the machine learning model.
 6. The methodof claim 1, wherein identifying each particular application furthercomprises: determining a category, of multiple categories, for each ofone or more potential applications; and adding, to the suggestions forone or more applications, a maximum amount of the one or more potentialapplications in one of the multiple categories, wherein at least one ofthe one or more potential applications is excluded from the suggestionsfor one or more applications due to the maximum amount already havingbeen reached for the category of that application.
 7. The method ofclaim 1, wherein the received user action includes identifying a userhand gesture that indicates the selected application, from thesuggestions, and drags an indication of the selected application toanother location in the artificial reality environment.
 8. The method ofclaim 1, wherein the obtaining components of the selected applicationcomprises: determining, based on which aspects of the selectedapplication will be used to provide the output in the artificial realityenvironment, a priority order for the components of the selectedapplication; and scheduling download of the components of the selectedapplication according to the priority order.
 9. The method of claim 1,wherein the permissions set for the selected application include two ormore of: permissions for creating augments in the artificial realityenvironment, permissions to provide notifications, permissions to accessinput signals, permissions to receive context features, permissions towrite into a shared XR space, permissions to exchange objects or otherdata with other authorized applications, or any combination thereof. 10.The method of claim 1, further comprising: identifying a user intent byidentifying that a user ignored or closed a threshold amount of outputsfrom the selected application within a time window; and in response toidentifying the user intent, removing one or more of the permissions setfor the selected application.
 11. A non-transitory computer-readablestorage medium storing instructions that, when executed by a computingsystem, cause the computing system to perform a process for suggesting,authorizing, and controlling application output in an artificial reality(XR) device, the process comprising: determining a plurality of featuresof a current XR context, defining a) characteristics of a user and b) anautomatically determined state of the real-world in a vicinity of theuser, the current XR context comprising one or more of: determinationsbased on sensor data, data retrieved from a third party source, datalocal to the XR device, or any combination thereof; providingsuggestions for one or more applications that match the current XRcontext, wherein each particular application is identified by:determining that a threshold subset of multiple features from theplurality of features of the current XR context have been mapped to theparticular application; or applying a machine learning model, trained todetermine a match score, to multiple features of the current XR contextand to a type specified for the particular application, and determiningthat a resulting match score is above a threshold; receiving a useraction to authorize a selected application of the suggested one or moreapplications; and in response to the user action, setting permissionsfor the selected application that allow the selected application toprovide output.
 12. The non-transitory computer-readable storage mediumof claim 11, wherein the process further comprises obtaining componentsof the selected application by: determining, based on which aspects ofthe selected application will be used to provide the output, a priorityorder for the components of the selected application; and schedulingdownload of the components of the selected application according to thepriority order.
 13. The non-transitory computer-readable storage mediumof claim 11, wherein the current XR context comprises: one or moreidentified objects, current location data for the XR device, andcalendar items for a current user.
 14. The non-transitorycomputer-readable storage medium of claim 11, wherein identifying theone or more applications is performed by the determining that thethreshold subset of features from the current XR context have beenmapped to the particular application.
 15. The non-transitorycomputer-readable storage medium of claim 11, wherein identifying theone or more applications is performed by the applying the machinelearning model.
 16. A computing system for suggesting, authorizing, andcontrolling application output in an artificial reality (XR) device, thecomputing system comprising: one or more processors; and one or morememories storing instructions that, when executed by the one or moreprocessors, cause the computing system to perform a process comprising:determining a plurality of features of a current XR context, defining a)characteristics of a user and b) an automatically determined state ofthe real-world in a vicinity of the user, the current XR contextcomprising one or more of: determinations based on sensor data, dataretrieved from a third party source, data local to the XR device, or anycombination thereof; providing suggestions for one or more applicationsthat match the current XR context, wherein each particular applicationis identified by: determining that a threshold subset of multiplefeatures from the plurality of features of the current XR context havebeen mapped to the particular application; or applying a machinelearning model, trained to determine a match score, to multiple featuresof the current XR context and to a type specified for the particularapplication, and determining that a resulting match score is above athreshold; receiving a user action to authorize a selected applicationof the suggested one or more applications; and in response to the useraction, setting permissions for the selected application that allow theselected application to provide output.
 17. The computing system ofclaim 16, wherein the received user action includes identifying a userhand gesture that indicates the selected application, from thesuggestions, and drags an indication of the selected application toanother location.
 18. The computing system of claim 16, whereinidentifying each particular application further comprises: determining acategory, of multiple categories, for each of one or more potentialapplications; and adding, to the suggestions for one or moreapplications, a maximum amount of the one or more potential applicationsin one of the multiple categories, wherein at least one of the one ormore potential applications is excluded from the suggestions for one ormore applications due to the maximum amount already having been reachedfor the category of that application.
 19. The computing system of claim16, wherein the permissions set for the selected application include twoor more of: permissions for creating augments, permissions to receivecontext features, permissions to exchange objects or other data withother authorized applications, or any combination thereof.
 20. Thecomputing system of claim 16, wherein the process further comprises:identifying a user intent by identifying that a user ignored or closed athreshold amount of outputs from the selected application; and inresponse to identifying the user intent, removing one or more of thepermissions set for the selected application.